迭代重建
计算机科学
投影(关系代数)
图像处理
算法
计算机视觉
绘图
计算机图形学
人工智能
图像(数学)
计算科学
计算机图形学(图像)
作者
Kun Wang,Chao Huang,Yu-Jiun Kao,Cheng‐Ying Chou,Alexander A. Oraevsky,Mark A. Anastasio
出处
期刊:Medical Physics
[Wiley]
日期:2013-01-28
卷期号:40 (2): 023301-023301
被引量:51
摘要
Purpose: Optoacoustic tomography (OAT) is inherently a three-dimensional (3D) inverse problem. However, most studies of OAT image reconstruction still employ two-dimensional imaging models. One important reason is because 3D image reconstruction is computationally burdensome. The aim of this work is to accelerate existing image reconstruction algorithms for 3D OAT by use of parallel programming techniques. Methods: Parallelization strategies are proposed to accelerate a filtered backprojection (FBP) algorithm and two different pairs of projection/backprojection operations that correspond to two different numerical imaging models. The algorithms are designed to fully exploit the parallel computing power of graphics processing units (GPUs). In order to evaluate the parallelization strategies for the projection/backprojection pairs, an iterative image reconstruction algorithm is implemented. Computer simulation and experimental studies are conducted to investigate the computational efficiency and numerical accuracy of the developed algorithms. Results: The GPU implementations improve the computational efficiency by factors of 1000, 125, and 250 for the FBP algorithm and the two pairs of projection/backprojection operators, respectively. Accurate images are reconstructed by use of the FBP and iterative image reconstruction algorithms from both computer-simulated and experimental data. Conclusions: Parallelization strategies for 3D OAT image reconstruction are proposed for the first time. These GPU-based implementations significantly reduce the computational time for 3D image reconstruction, complementing our earlier work on 3D OAT iterative image reconstruction.
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